Signal estimation | Trigonometry
In estimation theory, estimation of signal parameters via rotational invariant techniques (ESPRIT) is a technique to determine parameters of a mixture of sinusoids in a background noise. This technique is first proposed for frequency estimation, however, with the introduction of phased-array systems in daily use technology, it is also used for Angle of arrival estimations as well. (Wikipedia).
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Representing multivariate random signals using principal components. Principal component analysis identifies the basis vectors that describe the la
From playlist Random Signal Characterization
Characterization of Random, Multivariate Signals
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Multivariable (vector) probability density function representations, including the multivariate Gaussian density. The covariance matrix and in
From playlist Random Signal Characterization
Gilles Pagès: Optimal vector Quantization: from signal processing to clustering and ...
Abstract: Optimal vector quantization has been originally introduced in Signal processing as a discretization method of random signals, leading to an optimal trade-off between the speed of transmission and the quality of the transmitted signal. In machine learning, similar methods applied
From playlist Probability and Statistics
Notation and Basic Signal Properties
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Signals as functions, discrete- and continuous-time signals, sampling, images, periodic signals, displayi
From playlist Introduction and Background
Complex Stochastic Models and their Applications by Subhroshekhar Ghosh
PROGRAM: TOPICS IN HIGH DIMENSIONAL PROBABILITY ORGANIZERS: Anirban Basak (ICTS-TIFR, India) and Riddhipratim Basu (ICTS-TIFR, India) DATE & TIME: 02 January 2023 to 13 January 2023 VENUE: Ramanujan Lecture Hall This program will focus on several interconnected themes in modern probab
From playlist TOPICS IN HIGH DIMENSIONAL PROBABILITY
A Random Matrix Bayesian framework for out-of-sample quadratic optimization - Marc Potters
Marc Potters CFM November 6, 2013 For more videos, please visit http://video.ias.edu
From playlist Mathematics
Estimation of Coherence and Cross Spectra
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Averaging approaches for estimating coherence and cross spectra, analogous to Welch's averaged periodogram estimator of the power spectrum.
From playlist Estimation and Detection Theory
Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 3"
Graduate Summer School 2012: Deep Learning, Feature Learning "Scattering Invariant Deep Networks for Classification, Pt. 3" Stéphane Mallat, École Polytechnique Institute for Pure and Applied Mathematics, UCLA July 19, 2012 For more information: https://www.ipam.ucla.edu/programs/summer
From playlist GSS2012: Deep Learning, Feature Learning
Complex Stochastic Models and their Applications by Subhroshekhar Ghosh
PROGRAM: TOPICS IN HIGH DIMENSIONAL PROBABILITY ORGANIZERS: Anirban Basak (ICTS-TIFR, India) and Riddhipratim Basu (ICTS-TIFR, India) DATE & TIME: 02 January 2023 to 13 January 2023 VENUE: Ramanujan Lecture Hall This program will focus on several interconnected themes in modern probab
From playlist TOPICS IN HIGH DIMENSIONAL PROBABILITY
LenseFlow and the Bayesian delensing of CMB polarization - Anderes - Workshop 2 - CEB T3 2018
Ethan Anderes (University of California at Davis) / 22.10.2018 LenseFlow and the Bayesian delensing of CMB polarization ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoi
From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology
Introduction to Estimation Theory
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. General notion of estimating a parameter and measures of estimation quality including bias, variance, and mean-squared error.
From playlist Estimation and Detection Theory
Signal correlation functions for parameter estimation - A. Tilloy - Workshop 1 - CEB T2 2018
Antoine Tilloy (Max Plank Institut für Quantenoptik, Garching) / 17.05.2018 Signal correlation functions for parameter estimation When continuously measuring a quantum system, one is typically interested in reconstructing the quantum state in real time as a function of the measured signa
From playlist 2018 - T2 - Measurement and Control of Quantum Systems: Theory and Experiments
Maximum Likelihood Estimation Examples
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Three examples of applying the maximum likelihood criterion to find an estimator: 1) Mean and variance of an iid Gaussian, 2) Linear signal model in
From playlist Estimation and Detection Theory
Edouard Oyallon: One signal processing view on deep Learning - lecture 2
Since 2012, deep neural networks have led to outstanding results in many various applications, literally exceeding any previously existing methods, in texts, images, sounds, videos, graphs... They consist of a cascade of parametrized linear and non-linear operators whose parameters are opt
From playlist Mathematical Aspects of Computer Science
Random Processes and Stationarity
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduction to describing random processes using first and second moments (mean and autocorrelation/autocovariance). Definition of a stationa
From playlist Random Signal Characterization
Stéphane Mallat - Apprentissage par invariants en grande dimension
Apprentissage par invariants en grande dimension : de l’image ou de la musique à la chimie quantique Huawei-IHÉS Workshop on Mathematical Sciences Tuesday, May 5th 2015
From playlist Huawei-IHÉS Workshop on Mathematical Sciences
The Sample Complexity of Multi-Reference Alignment - Philippe Rigollet
Members' Seminar Topic: The Sample Complexity of Multi-Reference Alignment Speaker: Philippe Rigollet Affiliation: Massachusetts Institute of Technology; Visiting Professor, School of Mathematics Date: February 4, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
Joe Kileel - Method of moments in cryo-EM - IPAM at UCLA
Recorded 16 November 2022. Joe Kileel of the University of Texas at Austin presents "Method of moments in cryo-EM" at IPAM's Cryo-Electron Microscopy and Beyond Workshop. Abstract: In this talk, I will present recent advances in the theory and implementation of method of moments-based appr
From playlist 2022 Cryo-Electron Microscopy and Beyond
Reconstruction and the Sampling Theorem
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Analysis of the conditions under which a continuous-time signal can be reconstructed from its samples, including ideal bandlimited interpolati
From playlist Sampling and Reconstruction of Signals